scholarly journals THE NEW GENERALIZED GRAVITATIONAL MODEL OF MIGRATION FOR GEORGIA

2020 ◽  
pp. 130-137
Author(s):  
QETEVAN PIPIA ◽  
GOCHA TUTBERIDZE ◽  
GIVI RAKVIASHVILI ◽  
KRISTINE RAKVIASHVILI
Keyword(s):  
Mathematical Model ◽  
Linear Regression ◽  
European Countries ◽  
Electrostatic Attraction ◽  
Universal Gravitation ◽  
Dummy Variables ◽  
Gravitational Model ◽  
New Models ◽  
Different Temperatures ◽  
Law Of Attraction

Econophysics, or the theory of construction of models using physical assumptions in economics, already has a long history. For this purpose, the gravitational law of attraction was probably first used in the modeling of trade models between two subjects. The laws of gravitational and electrostatic attraction were then used to study migration between countries. The article adopts two new models (containing dummy variables) of migration from Georgia to leading European countries and USA using multivariate linear regression. They are based on the Lewer and van der Berg generalized gravitational model of migration between countries of The Organisation for Economic Co-operation and Development (OECD). Their model contains dummy parameters of border, the proximity of the state languages and colonial links in past. In this article we introduce a new dummy parameter «religion» of the model of migration from Georgia; It is hypothesized that migration between neighbor countries may not be analogous to the Newton›s law of universal gravitation. In our view, it would be more appropriate to use other physical assumptions to construct such a migration model, for example a mathematical model of the law of equalization of temperatures in an area with different temperatures at different points.

scholarly journals Relationship between MODIS Derived NDVI and Yield of Cereals for Selected European Countries

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 340
Author(s):  
Ewa Panek ◽  
Dariusz Gozdowski
Keyword(s):  
Linear Regression ◽  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Arable Land ◽  
Early Spring ◽  
European Countries ◽  
Yield Prediction ◽  
Country Level ◽  
Using Data

In this study, the relationships between normalized difference vegetation index (NDVI) obtained based on MODIS satellite data and grain yield of all cereals, wheat and barley at a country level were analyzed. The analysis was performed by using data from 2010–2018 for 20 European countries, where percentage of cereals is high (at least 35% of the arable land). The analysis was performed for each country separately and for all of the collected data together. The relationships between NDVI and cumulative NDVI (cNDVI) were analyzed by using linear regression. Relationships between NDVI in early spring and grain yield of cereals were very strong for Croatia, Czechia, Germany, Hungary, Latvia, Lithuania, Poland and Slovakia. This means that the yield prediction for these countries can be as far back as 4 months before the harvest. The increase of NDVI in early spring was related to the increase of grain yield by about 0.5–1.6 t/ha. The cumulative of averaged NDVI gives more stable prediction of grain yield per season. For France and Belgium, the relationships between NDVI and grain yield were very weak.

scholarly journals Analysis of Plant-Production-Obtained Biomass in Function of Sustainable Energy

2020 ◽  
Vol 12 (13) ◽  
pp. 5486
Author(s):  
Siniša Škrbić ◽  
Aleksandar Ašonja ◽  
Radivoj Prodanović ◽  
Vladica Ristić ◽  
Goran Stevanović ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Factor Analysis ◽  
Linear Regression ◽  
Plant Production ◽  
Renewable Source ◽  
Agricultural Biomass ◽  
Low Degree ◽  
Biomass Potential ◽  
Expected Benefits ◽  
Biomass For Energy

This research analyzed the degree of utilization of the agricultural biomass for energy purposes (combustion), in order to indicate the reasons that limit its use. The biomass potential was studied by means of the methodology of the biomass potential, whereas the factors suggesting a low degree of biomass utilization were identified by means of factor analysis. The research results reveal that there is an enormous potential of the unused agricultural biomass. This dissertation research significantly contributes to the establishment of a genuine mathematical model based on multiple linear regression. The solution obtained by this analysis, in both a mathematical and a scientific manner, conveys the primary reasons for an insufficient utilization of the biomass for energy purposes. Moreover, the paper suggests the measures to be applied for a more substantial use of this renewable source of energy and presents the expected benefits to be gained.

Methodology of Estimation of Fire Separation Distances between Construction Facilities by Calculation

2020 ◽  
Vol 1006 ◽  
pp. 93-100
Author(s):  
Vadym Nizhnyk ◽  
Yurii Feshchuk ◽  
Volodymyr Borovykov
Keyword(s):  
Mathematical Model ◽  
Heat Flux ◽  
Linear Regression ◽  
Ignition Temperature ◽  
Oil Products ◽  
Regression Equations ◽  
Fire Load ◽  
Literary Sources ◽  
Tabular Method

Based on analysis of appropriate literary sources we established that estimation of fire separation distances was based of two criteria: heat flux and temperature. We proposed to use “ignition temperature of materials” as principal criterion when determining fire separation distances between adjacent construction facilities. Based on the results derived while performing complete factorial we created mathematical model to describe trend of changing fire separation distances depending on caloric power of fire load (Q), openings factor of the external enclosing structures (k) and duration of irradiation (t); moreover, its adequacy was confirmed. Based on linear regression equations we substantiated calculation and tabular method for the determination of fire separation distances for a facility being irradiated which contains combustible or otherwise non-combustible façade and a facility where liquid oil products turn. We developed and proposed general methodology for estimation of fire separation distances between construction facilities by calculation.

Modeling of Liquid-Liquid Demixing Curve in Lead-Zinc Binary System

2018 ◽  
Vol 18 ◽  
pp. 49-54
Author(s):  
Naceur Amel ◽  
Adjadj Fouzia
Keyword(s):  
Mathematical Model ◽  
Free Energy ◽  
Phase Separation ◽  
Binary System ◽  
Free Energies ◽  
Common Tangent ◽  
Different Temperatures ◽  
Lead Zinc ◽  
The Common ◽  
Zn Alloys

In this work we discussed the modeling of the demixing curve in the liquid state in the Lead – Zinc binary system. We are interested to recalculate the free energies relating on Pb-Zn alloys for several temperatures based on the thermodynamic data collected in the bibliography. This calculation allows us to trace the curve of phase separation from a program after obtaining the mole fractions corresponding to the common tangent to the curve of the free energy with two minima at different temperatures. To do this, we used the Matlab 7.1 as the programming language and the Redlich-Kister polynomial as a mathematical model of development. The results obtained are very satisfactory by comparing them with those of the bibliography.

scholarly journals Shubnikov–de Haas Oscillations in Semiconductors at the Microwave-Radiation Absorption

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
G. Gulyamov ◽  
U. I. Erkaboev ◽  
A. G. Gulyamov
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Electromagnetic Field ◽  
Microwave Radiation ◽  
Three Dimensional ◽  
Radiation Absorption ◽  
Narrow Gap ◽  
Proposed Model ◽  
Different Temperatures ◽  
Shubnikov De Haas Oscillations

Mathematical models for the Shubnikov-de Haas oscillations in semiconductors are obtained at the microwave-radiation absorption and its temperature dependence. Three-dimensional image of microwave magnetoabsorption oscillations in narrow-gap semiconductors is established. Using a mathematical model, the oscillations of the microwave magnetoabsorption are considered for different values of the electromagnetic field. The results of calculations are compared with experimental data. The proposed model explains the experimental results in HgSe at different temperatures.

scholarly journals Self-Reported Autonomic Dysregulation in Gulf War Illness

2021 ◽  
Author(s):  
Timothy J Avery ◽  
Danielle C Mathersul ◽  
R Jay Schulz-Heik ◽  
Louise Mahoney ◽  
Peter J Bayley
Keyword(s):  
Mental Health ◽  
Linear Regression ◽  
Physical Functioning ◽  
Regression Models ◽  
Gulf War ◽  
Linear Regression Models ◽  
Gulf War Illness ◽  
Autonomic Dysregulation ◽  
Health Burden ◽  
New Models

ABSTRACT Introduction Autonomic nervous system dysregulation is commonly observed in Gulf War illness (GWI). Using a new sample, we sought to replicate and extend findings from a previous study that found autonomic symptoms predicted physical functioning in Veterans with GWI. Materials and Methods A linear regression model was used to predict physical functioning (36-item Short Form Health Survey (SF-36); n = 73, 75% male). First, we examined the predictive value of independent variables individually in the model including: the 31-item Composite Autonomic Symptom Score (COMPASS-31) total score, body mass index (BMI), mental health burden (i.e., post-traumatic stress disorder [PTSD] and/or depression), and COMPASS-31 subscales: orthostatic intolerance, vasomotor, secretomotor, gastrointestinal, bladder, and pupillomotor. Next, we estimated linear regression models containing the three variables (autonomic symptoms, BMI, and mental health burden) identified as predictors of physical functioning from the prior study. Results These linear regression models significantly predicted physical functioning and accounted for 15% of the variance with COMPASS-31, 36.6% of variance with COMPASS-31 and BMI, and 38.2% of variance with COMPASS-31, BMI, and mental health burden. Then, forward step-wise linear regressions were applied to explore new models including COMPASS-31 subscales. Two new models accounted for more of the variance in physical functioning: 39.3% with added gastrointestinal symptoms (β = −2.206, P = .001) and 43.4% of variance with both gastrointestinal (β = −1.592, P = .008) and secretomotor subscales (β = −1.533, P = .049). Unlike the previous study we intended to replicate, mental health burden was not a significant predictor in any of our models. Conclusions Treatments that address autonomic dysregulation should be prioritized for research and clinical recommendations for Veterans with GWI who experience chronic pain.

scholarly journals Mathematical model of transmission dynamics with mitigation and health measures for SARS-CoV-2 infection in European countries

2020 ◽  
Author(s):  
Shweta Sankhwar ◽  
Narender Kumar ◽  
Ravins Dohare
Keyword(s):  
Mathematical Model ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
European Countries ◽  
Transmission Dynamics ◽  
Second Phase ◽  
Geographical Regions ◽  
Two Phases ◽  
Spread Of Infection ◽  
And Control

Abstract The pandemic of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) continue to pose a serious threat to global health resulting in disease COVID-19. No specific drug or vaccine is available against this infection. Therefore, the prevention is only way to reduce the spread of infection. The pandemic needs an enhanced mathematical model, therefore, we propose a SEIAJR compartmental mathematical model to estimate the basic reproduction number (R0 ) and the transmission dynamics of four European countries (Germany, United Kingdom, Switzerland and Spain). The proposed mathematical model incorporates mitigation and healthcare measures as recommended by ECDC (European Centre for Disease Prevention and Control). The simulation of proposed model is done in two phases. First-phase simulation estimates basic reproduction number and mitigation rate according to active infected cases in all four European countries. R0 estimate 2.82 - 3.3 for considered European countries. Second-phase simulation predicts the dynamics of infection on the estimated R0 with varying mitigation rate and constant healthcare rate. This study predicts that no more mitigation is required to invade the infection. The current mitigation and healthcare measures are enough to stop the propogation of infection, however, infection would last by end of July 2020. The developed mathematical model would also be applicable to portray the infection trasmission dynamics for other geographical regions with varying parameters.

Cervix cancer regression measured using weekly MR imaging during fractionated radiotherapy: Radiobiologic modeling and correlation with tumor hypoxia

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 5547-5547
Author(s):  
K. S. Lim ◽  
P. Chan ◽  
R. Dinniwell ◽  
A. Fyles ◽  
M. Haider ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Regression Analysis ◽  
Linear Regression ◽  
Mr Imaging ◽  
Tumor Volume ◽  
Tumor Regression ◽  
Linear Regression Analysis ◽  
Tumor Hypoxia ◽  
Cervix Cancer ◽  
Pre Treatment

5547 Background: To utilize cervix cancer volumetry, as measured with MR imaging during definitive chemoirradiation (RT-CT), to derive radiobiological parameters using a mathematical model of tumor regression, and compare them to pre-treatment measurements of tumor hypoxia. Methods: Twenty-eight patients receiving RT-CT for cervix cancer underwent weekly magnetic resonance imaging (MRI) scans. Tumor volume was assessed on each of these scans and the rate of regression plotted. A mathematical model of tumor regression was formulated to simulate the relationship between three independent radiobiological parameters, 1) surviving fraction of cells after 2 Gy, SF2, 2) the cell clearance constant Tc, and 3) the cellular proliferation constant Tp. Non-linear regression analysis was applied to fit the MR-derived tumor volumes to the mathematical model and to derive SF2 and Tc values for each patient. These were compared to pre-treatment hypoxia measurements. Results: Initial tumor volume ranged between 8 and 209 cm3. Relative reduction in volume during treatment was 0.02 to 0.79. Simulations using representative values of the independent biologic variables derived from the literature showed SF2 and Tc to strongly influence the shape of the volume response curves. Non-linear regression analysis yielded a median SF2 of 0.71 and median Tc of 10 days. Radioresistant tumors (SF2 >0.71) were significantly more hypoxic at diagnosis (p=0.02). Conclusion: Based on serial MR imaging during treatment, a marked variation in cervix tumor regression is seen from patient to patient. Through our radiobiological model, tumors can be classified as radioresistant or radiosensitive, which correlates with hypoxia [Table: see text] No significant financial relationships to disclose.

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